Libreries to install:
#install.packages(“tidyverse”) .- tibble using and other tools #install.packages(“sf”) .- Geospatial data of several countries #install.packages(“maps”) .- USA Regions data #install.packages(“tools”) .- Different R utilites to use in graphic titles for example #install.packages(“utils”) .- Several R utilities #install.packages(“stringr”) .- handling of text strings #install.packages(“rnaturalearth”) .- Many countries data #install.packages(“rnaturalearthdata”).- Needed to create a great map #install.packages(“ggrepel”) .- Used for labels do not overlap on the map #install.packages(“magick”) .- To generate animations with pre-built maps #install.packages(“readxl”) .- for reading excel files #install.packages(“R.utils”).- To get several functions like isZero #install.packages(“patchwork”) #install.packages(“psych”) #install.packages(“MLmetrics”) #install.packages(“DiagrammeR”) ## Calling for the nedeed libraries:
library (yaml)
library(tidyverse)
library(sf)
library(maps)
library (tools)
library(utils)
library(stringr)
library(rnaturalearth)
library(rnaturalearthdata)
library(ggrepel)
library(transformr)
library(magick)
library(readxl)
library(lubridate)
library(gganimate)
#List for the years related to Air Quality Data
datayears = c("2017","2018","2019","2020")
# Defining variables for directories
prename="airdata"
airfilepath="./Data/Air_Quality/"
# If png does not exist then we create it
if (!(dir.exists("./png/")))
{dir.create("./png/")}
pngpath="./png/"
datapath="./Data/"
popfilepath="./Data/Population/"
imgpath="/images/"
Visitspath="./Data/Hospital_Visits/"
# Defining file names variables to load the data
filename="daily_aqi_by_county_"
Visitsfile="HCUP_SummaryTrendTables_T5a.xlsx"
filepop="nst-est2020-alldata.csv"
# Defining file names variables to save the data
file_aqi_save = "Air_Quality_Indexes.Rdata"
file_visits_save = "Hosp_visits_pop_by_state.Rdata"
#Generate not_in function for different uses
`%not_in%` <- purrr::negate(`%in%`)
Aggregate AQI USA County Data by Month per Year
Each NAAQS pollutant has a separate AQI scale, with an AQI rating of 100 corresponding to the concentration of the Federal Standard for that pollutant.
| # calling function to load and group Air quality data by 2017 to 2020: |
| ## Merging with geographical data for USA Counties, from packages(“sf”), and saving as RData: |
| ## Now representing Air Quality on a USA geographical detailed by county: |
Now saving maps as .png
Animate maps
Including animated GIF of the Air Quality cheks on a USA geographical counties
For the 2017 to 2020 years:

| ## Including geographical USA states data to attach to the Hospital visits dataset |
| # Generating a map with Hospital Visists per year and month |
Looping all created maps for a moving image
| ## Generating an animated map of Hospital Visists |

## # A tibble: 6 x 6
## REGION DIVISION STATE NAME POPULATION YEAR
## <chr> <chr> <int> <chr> <int> <dbl>
## 1 0 0 0 United States 325122128 2017
## 2 0 0 0 United States 326838199 2018
## 3 0 0 0 United States 328329953 2019
## 4 0 0 0 United States 329484123 2020
## 5 1 0 0 Northeast Region 56083383 2017
## 6 1 0 0 Northeast Region 56084543 2018